Modeling of Human Upper Body for Sign Language Recognition

Author

Bilal, Sara ; Akmeliawati, Rini ; Shafie, Amir A. ; Salami, M.J.E.

Author_Institution

Dept. of Mechatron. Eng., Int. Islamic Univ. Malaysia (IIUM), Kuala Lumpur, Malaysia

fYear

2011

fDate

6-8 Dec. 2011

Firstpage

104

Lastpage

108

Abstract

Sign Language Recognition systems require not only the hand motion trajectory to be classified but also facial features, Human Upper Body (HUB) and hand position with respect to other HUB parts. Head, face, forehead, shoulders and chest are very crucial parts that can carry a lot of positioning information of hand gestures in gesture classification. In this paper as the main contribution, a fast and robust search algorithm for HUB parts based on head size has been introduced for real time implementations. Scaling the extracted parts during body orientation was attained using partial estimation of face size. Tracking the extracted parts for front and side view was achieved using CAMSHIFT [24]. The outcome of the system makes it applicable for real-time applications such as Sign Languages Recognition (SLR) systems.

Keywords

gesture recognition; image classification; CAMSHIFT; HUB parts; chest; face size partial estimation; facial features; forehead; gesture classification; hand gestures; hand position; head size; human upper body modeling; shoulders; sign language recognition system; Computational modeling; Face; Feature extraction; Humans; Real time systems; Tracking; Human upper body detection; Scaling; Sign Language Recognition; Tracking using CAMSHIFT;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation, Robotics and Applications (ICARA), 2011 5th International Conference on

Conference_Location

Wellington

Print_ISBN

978-1-4577-0329-4

Type

conf

DOI

10.1109/ICARA.2011.6144865

Filename

6144865